fofr/any-comfyui-workflow-a100
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any-comfyui-workflow-a100
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fofr/any-comfyui-workflow-a100
Run any ComfyUI workflow on an A100. Guide: https://github.com/fofr/cog-comfyui
fofr/star-trek-flan
flan-t5-xl trained on the Memory Alpha Star Trek Wiki
fofr/star-trek-gpt-j-6b
gpt-j-6b trained on the Memory Alpha Star Trek Wiki
fofr/star-trek-llama
llama-7b trained on the Memory Alpha Star Trek Wiki
fofr/star-trek-adventure
fofr/image-prompts
Generate image prompts for Midjourney. Prefix inputs with "Image: "
fofr/video-to-frames
Split a video into frames
fofr/frames-to-video
Convert a set of frames to a video
fofr/damo-text2video
fofr/audio-to-waveform
Create a waveform video from audio
fofr/sdxl-tron
A fine-tuned SDXL lora based on Tron Legacy
fofr/sdxl-barbie
A fine-tuned SDXL lora based on the Barbie movie
fofr/sdxl-mario-kart
fofr/sdxl-sonic-2
fofr/sdxl-text
Exploratory SDXL fine-tuning on text "FOFR"
fofr/sdxl-barbietron
SDXL fine-tuned on both Barbie and Tron Legacy
fofr/sdxl-vision-pro
An SDXL fine-tune on Apple Vision Pro
fofr/sdxl-cats-movie
fofr/sdxl-matrix-code
An SDXL fine-tune based on Matrix Code art
fofr/sdxl-simpsons
fofr/sdxl-demo
Run any ComfyUI workflow on an A100. Guide: https://github.com/fofr/cog-comfyui
Prediction
fofr/any-comfyui-workflow-a100:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9IDccwrv7mvpnrj00chpbxagpjg2cStatusSucceededSourceWebHardwareA100 (80GB)Total durationCreatedInput
- output_format
- webp
- workflow_json
- { "3": { "inputs": { "seed": 156680208700286, "steps": 10, "cfg": 2.5, "sampler_name": "dpmpp_2m_sde", "scheduler": "karras", "denoise": 1, "model": [ "4", 0 ], "positive": [ "6", 0 ], "negative": [ "7", 0 ], "latent_image": [ "5", 0 ] }, "class_type": "KSampler", "_meta": { "title": "KSampler" } }, "4": { "inputs": { "ckpt_name": "SDXL-Flash.safetensors" }, "class_type": "CheckpointLoaderSimple", "_meta": { "title": "Load Checkpoint" } }, "5": { "inputs": { "width": 1024, "height": 1024, "batch_size": 1 }, "class_type": "EmptyLatentImage", "_meta": { "title": "Empty Latent Image" } }, "6": { "inputs": { "text": "beautiful scenery nature glass bottle landscape, purple galaxy bottle,", "clip": [ "4", 1 ] }, "class_type": "CLIPTextEncode", "_meta": { "title": "CLIP Text Encode (Prompt)" } }, "7": { "inputs": { "text": "text, watermark", "clip": [ "4", 1 ] }, "class_type": "CLIPTextEncode", "_meta": { "title": "CLIP Text Encode (Prompt)" } }, "8": { "inputs": { "samples": [ "3", 0 ], "vae": [ "4", 2 ] }, "class_type": "VAEDecode", "_meta": { "title": "VAE Decode" } }, "9": { "inputs": { "filename_prefix": "ComfyUI", "images": [ "8", 0 ] }, "class_type": "SaveImage", "_meta": { "title": "Save Image" } } }
- output_quality
- 95
- randomise_seeds
- force_reset_cache
- return_temp_files
{ "output_format": "webp", "workflow_json": "{\n \"3\": {\n \"inputs\": {\n \"seed\": 156680208700286,\n \"steps\": 10,\n \"cfg\": 2.5,\n \"sampler_name\": \"dpmpp_2m_sde\",\n \"scheduler\": \"karras\",\n \"denoise\": 1,\n \"model\": [\n \"4\",\n 0\n ],\n \"positive\": [\n \"6\",\n 0\n ],\n \"negative\": [\n \"7\",\n 0\n ],\n \"latent_image\": [\n \"5\",\n 0\n ]\n },\n \"class_type\": \"KSampler\",\n \"_meta\": {\n \"title\": \"KSampler\"\n }\n },\n \"4\": {\n \"inputs\": {\n \"ckpt_name\": \"SDXL-Flash.safetensors\"\n },\n \"class_type\": \"CheckpointLoaderSimple\",\n \"_meta\": {\n \"title\": \"Load Checkpoint\"\n }\n },\n \"5\": {\n \"inputs\": {\n \"width\": 1024,\n \"height\": 1024,\n \"batch_size\": 1\n },\n \"class_type\": \"EmptyLatentImage\",\n \"_meta\": {\n \"title\": \"Empty Latent Image\"\n }\n },\n \"6\": {\n \"inputs\": {\n \"text\": \"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"7\": {\n \"inputs\": {\n \"text\": \"text, watermark\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"8\": {\n \"inputs\": {\n \"samples\": [\n \"3\",\n 0\n ],\n \"vae\": [\n \"4\",\n 2\n ]\n },\n \"class_type\": \"VAEDecode\",\n \"_meta\": {\n \"title\": \"VAE Decode\"\n }\n },\n \"9\": {\n \"inputs\": {\n \"filename_prefix\": \"ComfyUI\",\n \"images\": [\n \"8\",\n 0\n ]\n },\n \"class_type\": \"SaveImage\",\n \"_meta\": {\n \"title\": \"Save Image\"\n }\n }\n}\n", "output_quality": 95, "randomise_seeds": true, "force_reset_cache": false, "return_temp_files": false }Install Replicate’s Node.js client library:npm install replicateImport and set up the client:import Replicate from "replicate"; import fs from "node:fs"; const replicate = new Replicate({ auth: process.env.REPLICATE_API_TOKEN, });Run fofr/any-comfyui-workflow-a100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "fofr/any-comfyui-workflow-a100:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9", { input: { output_format: "webp", workflow_json: "{\n \"3\": {\n \"inputs\": {\n \"seed\": 156680208700286,\n \"steps\": 10,\n \"cfg\": 2.5,\n \"sampler_name\": \"dpmpp_2m_sde\",\n \"scheduler\": \"karras\",\n \"denoise\": 1,\n \"model\": [\n \"4\",\n 0\n ],\n \"positive\": [\n \"6\",\n 0\n ],\n \"negative\": [\n \"7\",\n 0\n ],\n \"latent_image\": [\n \"5\",\n 0\n ]\n },\n \"class_type\": \"KSampler\",\n \"_meta\": {\n \"title\": \"KSampler\"\n }\n },\n \"4\": {\n \"inputs\": {\n \"ckpt_name\": \"SDXL-Flash.safetensors\"\n },\n \"class_type\": \"CheckpointLoaderSimple\",\n \"_meta\": {\n \"title\": \"Load Checkpoint\"\n }\n },\n \"5\": {\n \"inputs\": {\n \"width\": 1024,\n \"height\": 1024,\n \"batch_size\": 1\n },\n \"class_type\": \"EmptyLatentImage\",\n \"_meta\": {\n \"title\": \"Empty Latent Image\"\n }\n },\n \"6\": {\n \"inputs\": {\n \"text\": \"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"7\": {\n \"inputs\": {\n \"text\": \"text, watermark\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"8\": {\n \"inputs\": {\n \"samples\": [\n \"3\",\n 0\n ],\n \"vae\": [\n \"4\",\n 2\n ]\n },\n \"class_type\": \"VAEDecode\",\n \"_meta\": {\n \"title\": \"VAE Decode\"\n }\n },\n \"9\": {\n \"inputs\": {\n \"filename_prefix\": \"ComfyUI\",\n \"images\": [\n \"8\",\n 0\n ]\n },\n \"class_type\": \"SaveImage\",\n \"_meta\": {\n \"title\": \"Save Image\"\n }\n }\n}\n", output_quality: 95, randomise_seeds: true, force_reset_cache: false, return_temp_files: false } } ); // To access the file URL: console.log(output[0].url()); //=> "http://example.com" // To write the file to disk: fs.writeFile("my-image.png", output[0]);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:pip install replicateImport the client:import replicateRun fofr/any-comfyui-workflow-a100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "fofr/any-comfyui-workflow-a100:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9", input={ "output_format": "webp", "workflow_json": "{\n \"3\": {\n \"inputs\": {\n \"seed\": 156680208700286,\n \"steps\": 10,\n \"cfg\": 2.5,\n \"sampler_name\": \"dpmpp_2m_sde\",\n \"scheduler\": \"karras\",\n \"denoise\": 1,\n \"model\": [\n \"4\",\n 0\n ],\n \"positive\": [\n \"6\",\n 0\n ],\n \"negative\": [\n \"7\",\n 0\n ],\n \"latent_image\": [\n \"5\",\n 0\n ]\n },\n \"class_type\": \"KSampler\",\n \"_meta\": {\n \"title\": \"KSampler\"\n }\n },\n \"4\": {\n \"inputs\": {\n \"ckpt_name\": \"SDXL-Flash.safetensors\"\n },\n \"class_type\": \"CheckpointLoaderSimple\",\n \"_meta\": {\n \"title\": \"Load Checkpoint\"\n }\n },\n \"5\": {\n \"inputs\": {\n \"width\": 1024,\n \"height\": 1024,\n \"batch_size\": 1\n },\n \"class_type\": \"EmptyLatentImage\",\n \"_meta\": {\n \"title\": \"Empty Latent Image\"\n }\n },\n \"6\": {\n \"inputs\": {\n \"text\": \"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"7\": {\n \"inputs\": {\n \"text\": \"text, watermark\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"8\": {\n \"inputs\": {\n \"samples\": [\n \"3\",\n 0\n ],\n \"vae\": [\n \"4\",\n 2\n ]\n },\n \"class_type\": \"VAEDecode\",\n \"_meta\": {\n \"title\": \"VAE Decode\"\n }\n },\n \"9\": {\n \"inputs\": {\n \"filename_prefix\": \"ComfyUI\",\n \"images\": [\n \"8\",\n 0\n ]\n },\n \"class_type\": \"SaveImage\",\n \"_meta\": {\n \"title\": \"Save Image\"\n }\n }\n}\n", "output_quality": 95, "randomise_seeds": True, "force_reset_cache": False, "return_temp_files": False } ) # To access the file URL: print(output[0].url()) #=> "http://example.com" # To write the file to disk: with open("my-image.png", "wb") as file: file.write(output[0].read())To learn more, take a look at the guide on getting started with Python.
Run fofr/any-comfyui-workflow-a100 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \ -H "Authorization: Bearer $REPLICATE_API_TOKEN" \ -H "Content-Type: application/json" \ -H "Prefer: wait" \ -d $'{ "version": "fofr/any-comfyui-workflow-a100:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9", "input": { "output_format": "webp", "workflow_json": "{\\n \\"3\\": {\\n \\"inputs\\": {\\n \\"seed\\": 156680208700286,\\n \\"steps\\": 10,\\n \\"cfg\\": 2.5,\\n \\"sampler_name\\": \\"dpmpp_2m_sde\\",\\n \\"scheduler\\": \\"karras\\",\\n \\"denoise\\": 1,\\n \\"model\\": [\\n \\"4\\",\\n 0\\n ],\\n \\"positive\\": [\\n \\"6\\",\\n 0\\n ],\\n \\"negative\\": [\\n \\"7\\",\\n 0\\n ],\\n \\"latent_image\\": [\\n \\"5\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"KSampler\\",\\n \\"_meta\\": {\\n \\"title\\": \\"KSampler\\"\\n }\\n },\\n \\"4\\": {\\n \\"inputs\\": {\\n \\"ckpt_name\\": \\"SDXL-Flash.safetensors\\"\\n },\\n \\"class_type\\": \\"CheckpointLoaderSimple\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Load Checkpoint\\"\\n }\\n },\\n \\"5\\": {\\n \\"inputs\\": {\\n \\"width\\": 1024,\\n \\"height\\": 1024,\\n \\"batch_size\\": 1\\n },\\n \\"class_type\\": \\"EmptyLatentImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Empty Latent Image\\"\\n }\\n },\\n \\"6\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"7\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"text, watermark\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"8\\": {\\n \\"inputs\\": {\\n \\"samples\\": [\\n \\"3\\",\\n 0\\n ],\\n \\"vae\\": [\\n \\"4\\",\\n 2\\n ]\\n },\\n \\"class_type\\": \\"VAEDecode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"VAE Decode\\"\\n }\\n },\\n \\"9\\": {\\n \\"inputs\\": {\\n \\"filename_prefix\\": \\"ComfyUI\\",\\n \\"images\\": [\\n \\"8\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"SaveImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Save Image\\"\\n }\\n }\\n}\\n", "output_quality": 95, "randomise_seeds": true, "force_reset_cache": false, "return_temp_files": false } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/fofr/any-comfyui-workflow-a100@sha256:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9 \ -i 'output_format="webp"' \ -i $'workflow_json="{\\n \\"3\\": {\\n \\"inputs\\": {\\n \\"seed\\": 156680208700286,\\n \\"steps\\": 10,\\n \\"cfg\\": 2.5,\\n \\"sampler_name\\": \\"dpmpp_2m_sde\\",\\n \\"scheduler\\": \\"karras\\",\\n \\"denoise\\": 1,\\n \\"model\\": [\\n \\"4\\",\\n 0\\n ],\\n \\"positive\\": [\\n \\"6\\",\\n 0\\n ],\\n \\"negative\\": [\\n \\"7\\",\\n 0\\n ],\\n \\"latent_image\\": [\\n \\"5\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"KSampler\\",\\n \\"_meta\\": {\\n \\"title\\": \\"KSampler\\"\\n }\\n },\\n \\"4\\": {\\n \\"inputs\\": {\\n \\"ckpt_name\\": \\"SDXL-Flash.safetensors\\"\\n },\\n \\"class_type\\": \\"CheckpointLoaderSimple\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Load Checkpoint\\"\\n }\\n },\\n \\"5\\": {\\n \\"inputs\\": {\\n \\"width\\": 1024,\\n \\"height\\": 1024,\\n \\"batch_size\\": 1\\n },\\n \\"class_type\\": \\"EmptyLatentImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Empty Latent Image\\"\\n }\\n },\\n \\"6\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"7\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"text, watermark\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"8\\": {\\n \\"inputs\\": {\\n \\"samples\\": [\\n \\"3\\",\\n 0\\n ],\\n \\"vae\\": [\\n \\"4\\",\\n 2\\n ]\\n },\\n \\"class_type\\": \\"VAEDecode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"VAE Decode\\"\\n }\\n },\\n \\"9\\": {\\n \\"inputs\\": {\\n \\"filename_prefix\\": \\"ComfyUI\\",\\n \\"images\\": [\\n \\"8\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"SaveImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Save Image\\"\\n }\\n }\\n}\\n"' \ -i 'output_quality=95' \ -i 'randomise_seeds=true' \ -i 'force_reset_cache=false' \ -i 'return_temp_files=false'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/fofr/any-comfyui-workflow-a100@sha256:3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "output_format": "webp", "workflow_json": "{\\n \\"3\\": {\\n \\"inputs\\": {\\n \\"seed\\": 156680208700286,\\n \\"steps\\": 10,\\n \\"cfg\\": 2.5,\\n \\"sampler_name\\": \\"dpmpp_2m_sde\\",\\n \\"scheduler\\": \\"karras\\",\\n \\"denoise\\": 1,\\n \\"model\\": [\\n \\"4\\",\\n 0\\n ],\\n \\"positive\\": [\\n \\"6\\",\\n 0\\n ],\\n \\"negative\\": [\\n \\"7\\",\\n 0\\n ],\\n \\"latent_image\\": [\\n \\"5\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"KSampler\\",\\n \\"_meta\\": {\\n \\"title\\": \\"KSampler\\"\\n }\\n },\\n \\"4\\": {\\n \\"inputs\\": {\\n \\"ckpt_name\\": \\"SDXL-Flash.safetensors\\"\\n },\\n \\"class_type\\": \\"CheckpointLoaderSimple\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Load Checkpoint\\"\\n }\\n },\\n \\"5\\": {\\n \\"inputs\\": {\\n \\"width\\": 1024,\\n \\"height\\": 1024,\\n \\"batch_size\\": 1\\n },\\n \\"class_type\\": \\"EmptyLatentImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Empty Latent Image\\"\\n }\\n },\\n \\"6\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"7\\": {\\n \\"inputs\\": {\\n \\"text\\": \\"text, watermark\\",\\n \\"clip\\": [\\n \\"4\\",\\n 1\\n ]\\n },\\n \\"class_type\\": \\"CLIPTextEncode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"CLIP Text Encode (Prompt)\\"\\n }\\n },\\n \\"8\\": {\\n \\"inputs\\": {\\n \\"samples\\": [\\n \\"3\\",\\n 0\\n ],\\n \\"vae\\": [\\n \\"4\\",\\n 2\\n ]\\n },\\n \\"class_type\\": \\"VAEDecode\\",\\n \\"_meta\\": {\\n \\"title\\": \\"VAE Decode\\"\\n }\\n },\\n \\"9\\": {\\n \\"inputs\\": {\\n \\"filename_prefix\\": \\"ComfyUI\\",\\n \\"images\\": [\\n \\"8\\",\\n 0\\n ]\\n },\\n \\"class_type\\": \\"SaveImage\\",\\n \\"_meta\\": {\\n \\"title\\": \\"Save Image\\"\\n }\\n }\\n}\\n", "output_quality": 95, "randomise_seeds": true, "force_reset_cache": false, "return_temp_files": false } }' \ http://localhost:5000/predictionsTo learn more, take a look at the Cog documentation.
Output
{ "completed_at": "2024-09-02T13:44:16.317224Z", "created_at": "2024-09-02T13:44:14.005000Z", "data_removed": false, "error": null, "id": "ccwrv7mvpnrj00chpbxagpjg2c", "input": { "output_format": "webp", "workflow_json": "{\n \"3\": {\n \"inputs\": {\n \"seed\": 156680208700286,\n \"steps\": 10,\n \"cfg\": 2.5,\n \"sampler_name\": \"dpmpp_2m_sde\",\n \"scheduler\": \"karras\",\n \"denoise\": 1,\n \"model\": [\n \"4\",\n 0\n ],\n \"positive\": [\n \"6\",\n 0\n ],\n \"negative\": [\n \"7\",\n 0\n ],\n \"latent_image\": [\n \"5\",\n 0\n ]\n },\n \"class_type\": \"KSampler\",\n \"_meta\": {\n \"title\": \"KSampler\"\n }\n },\n \"4\": {\n \"inputs\": {\n \"ckpt_name\": \"SDXL-Flash.safetensors\"\n },\n \"class_type\": \"CheckpointLoaderSimple\",\n \"_meta\": {\n \"title\": \"Load Checkpoint\"\n }\n },\n \"5\": {\n \"inputs\": {\n \"width\": 1024,\n \"height\": 1024,\n \"batch_size\": 1\n },\n \"class_type\": \"EmptyLatentImage\",\n \"_meta\": {\n \"title\": \"Empty Latent Image\"\n }\n },\n \"6\": {\n \"inputs\": {\n \"text\": \"beautiful scenery nature glass bottle landscape, purple galaxy bottle,\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"7\": {\n \"inputs\": {\n \"text\": \"text, watermark\",\n \"clip\": [\n \"4\",\n 1\n ]\n },\n \"class_type\": \"CLIPTextEncode\",\n \"_meta\": {\n \"title\": \"CLIP Text Encode (Prompt)\"\n }\n },\n \"8\": {\n \"inputs\": {\n \"samples\": [\n \"3\",\n 0\n ],\n \"vae\": [\n \"4\",\n 2\n ]\n },\n \"class_type\": \"VAEDecode\",\n \"_meta\": {\n \"title\": \"VAE Decode\"\n }\n },\n \"9\": {\n \"inputs\": {\n \"filename_prefix\": \"ComfyUI\",\n \"images\": [\n \"8\",\n 0\n ]\n },\n \"class_type\": \"SaveImage\",\n \"_meta\": {\n \"title\": \"Save Image\"\n }\n }\n}\n", "output_quality": 95, "randomise_seeds": true, "force_reset_cache": false, "return_temp_files": false }, "logs": "Checking inputs\n====================================\nChecking weights\n✅ SDXL-Flash.safetensors exists in ComfyUI/models/checkpoints\n====================================\nRandomising seed to 1228588751\nRunning workflow\ngot prompt\nExecuting node 3, title: KSampler, class type: KSampler\n 0%| | 0/10 [00:00<?, ?it/s]\n 10%|█ | 1/10 [00:00<00:01, 6.62it/s]\n 20%|██ | 2/10 [00:00<00:01, 6.25it/s]\n 30%|███ | 3/10 [00:00<00:01, 6.11it/s]\n 40%|████ | 4/10 [00:00<00:00, 6.02it/s]\n 50%|█████ | 5/10 [00:00<00:00, 5.94it/s]\n 60%|██████ | 6/10 [00:00<00:00, 5.96it/s]\n 70%|███████ | 7/10 [00:01<00:00, 6.01it/s]\n 80%|████████ | 8/10 [00:01<00:00, 6.11it/s]\n 90%|█████████ | 9/10 [00:01<00:00, 6.42it/s]\n100%|██████████| 10/10 [00:01<00:00, 6.77it/s]\n100%|██████████| 10/10 [00:01<00:00, 6.31it/s]\nExecuting node 8, title: VAE Decode, class type: VAEDecode\nExecuting node 9, title: Save Image, class type: SaveImage\nPrompt executed in 1.92 seconds\noutputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}}\n====================================\nComfyUI_00001_.png", "metrics": { "predict_time": 2.301965796, "total_time": 2.312224 }, "output": [ "https://replicate.delivery/yhqm/NwatnTQUUFaPB9G3XNnzzrkOxN3pakhe4dOdEDInQ9fwM3YTA/ComfyUI_00001_.webp" ], "started_at": "2024-09-02T13:44:14.015258Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/ccwrv7mvpnrj00chpbxagpjg2c", "cancel": "https://api.replicate.com/v1/predictions/ccwrv7mvpnrj00chpbxagpjg2c/cancel" }, "version": "3e46e50649e491a94de614d02a68f92a8f35fd14785dd1264a49680039f094f9" }Generated inChecking inputs ==================================== Checking weights ✅ SDXL-Flash.safetensors exists in ComfyUI/models/checkpoints ==================================== Randomising seed to 1228588751 Running workflow got prompt Executing node 3, title: KSampler, class type: KSampler 0%| | 0/10 [00:00<?, ?it/s] 10%|█ | 1/10 [00:00<00:01, 6.62it/s] 20%|██ | 2/10 [00:00<00:01, 6.25it/s] 30%|███ | 3/10 [00:00<00:01, 6.11it/s] 40%|████ | 4/10 [00:00<00:00, 6.02it/s] 50%|█████ | 5/10 [00:00<00:00, 5.94it/s] 60%|██████ | 6/10 [00:00<00:00, 5.96it/s] 70%|███████ | 7/10 [00:01<00:00, 6.01it/s] 80%|████████ | 8/10 [00:01<00:00, 6.11it/s] 90%|█████████ | 9/10 [00:01<00:00, 6.42it/s] 100%|██████████| 10/10 [00:01<00:00, 6.77it/s] 100%|██████████| 10/10 [00:01<00:00, 6.31it/s] Executing node 8, title: VAE Decode, class type: VAEDecode Executing node 9, title: Save Image, class type: SaveImage Prompt executed in 1.92 seconds outputs: {'9': {'images': [{'filename': 'ComfyUI_00001_.png', 'subfolder': '', 'type': 'output'}]}} ==================================== ComfyUI_00001_.png
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